Triple
T8634541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoche |
E204487
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Pantin |
E613621
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Pantin | Statement: [Hoche, hasCity, Pantin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pantin Context triple: [Hoche, hasCity, Pantin]
-
A.
Pantin
chosen
Pantin is a northeastern suburb of Paris in the Seine-Saint-Denis department, known for its mix of residential areas, cultural venues, and redeveloped industrial zones along the Canal de l’Ourcq.
-
B.
Fontenay-aux-Roses
Fontenay-aux-Roses is a suburban commune in the southern outskirts of Paris, France, known for its residential character and historical ties to notable French artists and intellectuals.
-
C.
Villeray
Villeray is a residential neighborhood in Montreal, Quebec, known for its diverse population, local shops, and proximity to Jarry Park.
-
D.
Trappes
Trappes is a suburban commune in north-central France, located in the Yvelines department within the Île-de-France region near Paris.
-
E.
Clichy
Clichy is a suburban commune in the northwestern outskirts of Paris, France, known for its dense urban character and role as a residential and business hub.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc475fb9dc8190bd0d6e5edd05ea79 |
completed | March 31, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cecca2a3e48190b74ed3c948196409 |
completed | April 2, 2026, 8:08 p.m. |
Created at: March 30, 2026, 6:27 p.m.